Evaluation of a biopsychosocial education resource for mild traumatic brain injury: a mixed method exploratory study
Bibliographic record
Abstract
Introduction Education is strongly advocated as a key component of treatment for mild traumatic brain injury (mTBI) in clinical guidelines. However, there is mixed evidence on the benefit of education. This study aimed to evaluate a new education resource for mTBI. CLARITY is a freely available animated video based on a biopsychosocial conceptualization of mTBI, explaining the complex psychological, environmental and biological mechanisms behind symptoms and recovery. 1 Methods 24 adults with a history of mTBI participated in this mixed method study to examine prior experience of mTBI education and to evaluate CLARITY. Following viewing of the education video participants’ were invited to engage in a semi-structured interview and to share their perceptions of it via an online anonymous questionnaire. Results Thematic analysis of semi-structured interviews revealed one overarching theme: education is the foundation of recovery. Participants emphasised the critical role of coherent education in facilitating understanding, engagement in rehabilitation, and positive expectations during recovery. However, the first subtheme was that existing foundations are weak. Participants’ previous education was often limited in scope, inconsistent, and delivered in inaccessible ways. The second subtheme was that new foundations are stronger. Participants responded positively to CLARITY, highlighting its explanatory biopsychosocial approach, focus on mental health factors and accessible delivery methods as key strengths. Questionnaire responses revealed favourable endorsement of CLARITY’s utility, comprehensibility and accessibility. Discussion Recommendations for minor refinements to CLARITY were provided and made, as well as for its use in health care services.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".